12 citations · 17 across the 5 of their papers we have counts for
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cs.LG2025
Skrull: Towards Efficient Long Context Fine-tuning through Dynamic Data Scheduling
Hongtao Xu, Wenting Shen, Yuanxin Wei +6
Long-context supervised fine-tuning (Long-SFT) plays a vital role in enhancing the performance of large language models (LLMs) on long-context tasks. To smoothly adapt LLMs to long…
cs.CV2025★ 12 cited
Wan: Open and Advanced Large-Scale Video Generative Models
Team Wan, Ang Wang, Baole Ai +58
This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transfo…
cs.DC2025
Efficient Long Context Fine-tuning with Chunk Flow
Xiulong Yuan, Hongtao Xu, Wenting Shen +10
Long context fine-tuning of large language models(LLMs) involves training on datasets that are predominantly composed of short sequences and a small proportion of longer sequences.…